One of the tools a clinician has in disease diagnosis and treatment is genetic testing. To generate value in genetic testing, the link between genetic variants and disease must be discovered, documented, and shared within the community. Working with two existing genomic variation tools, Kafeen and Cordova, a new set of features referred to as Variant-Curation and Database Instantiation (Variant-CADI) was identified, designed, implemented and integrated into the existing Cordova system to unite data collection, management and distribution into one cohesive tool accessible through user interfaces. This eliminates the user needing specialized knowledge of the underlying implementation, data pipeline or data management to collect desired disease specific genetic variations. Using this tool, new disease-specific variation database instances have been initialized and created as demonstrations of the utility of these applications.

abstract: Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates. This can make mutation detection difficult; and while increasing sequencing depth can often help, sequence-specific errors and other non-random biases cannot be de- tected by increased depth. The problem of accurate genotyping is exacerbated when there is not a reference genome or other auxiliary information available. I explore several methods for sensitively detecting mutations in non-model or- ganisms using an example Eucalyptus melliodora individual. I use the structure of the tree to find bounds on its somatic mutation rate and evaluate several algorithms for variant calling. I find that conventional methods are suitable if the genome of a close relative can be adapted to the study organism. However, with structured data, a likelihood framework that is aware of this structure is more accurate. I use the techniques developed here to evaluate a reference-free variant calling algorithm. I also use this data to evaluate a k-mer based base quality score recalibrator (KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing data. Base quality scores can help detect errors in sequencing reads, but are often inaccurate. The most popular method for correcting this issue requires a known set of variant sites, which is unavailable in most cases. I simulate data and show that errors in this set of variant sites can cause calibration errors. I then show that KBBQ accurately recalibrates base quality scores while requiring no reference or other information and performs as well as other methods. Finally, I use the Eucalyptus data to investigate the impact of quality score calibra- tion on the quality of output variant calls and show that improved base quality score calibration increases the sensitivity and reduces the false positive rate of a variant calling algorithm. / Dissertation/Thesis / Doctoral Dissertation Molecular and Cellular Biology 2020

This master thesis deals with the determination of the variant prices for the public construction contract. The thesis is divided into the theoretical and practical part. The theoretical part analyses prices, construction contracts and budgets in general. Public construction contract for the residential building in Štěpánov was selected for this thesis. In the practical part the construction contract and the supplier company are briefly described. The price of the construction contract is analysed in the price analysis, where the budgets of the contracting authority and the selected supplier are compared. Based on this analysis, alternatives of material usage are suggested. At the end of the thesis the overall economic evaluation is carried out and the variant price of the contract is determined.

Mosaicism occurs due to postzygotic genetic alterations during early embryonic development. The phenomenon is common, present in all humans, animals, and plants, and is associated with phenotypic variability and heterogeneity. Mosaic pathogenic gene variants result in a mosaic disease state, in which the individual can present with mild, generalized disease, a localized disease phenotype in specific organs and tissue regions, or full-blown clinical features which are indistinguishable from the heterozygous disease state. Multiple studies have described the prevalence and clinical correlations associated with low-level mosaicism for various genetic disorders, including several tumor suppressor gene (TSG) syndromes, which are well-known to display mosaicism. However, the extent of mosaicism research varies widely between TSG syndromes. Currently there is no comprehensive, up to date review covering multiple TSGs and focusing on mosaicism prevalence, diagnostic strategies and transmission risk. Here, in this literature review, I focus on 8 common tumor suppressor genes NF1, NF2, TSC1, TSC2, RB1, PTEN, VHL, and TP53; reporting the following disease aspects: • Role and function of each tumor suppressor gene, disease prevalence, inheritance pattern, penetrance/expressivity pattern, age of onset clinical features, organs affected, and benign or malignant tumors seen • Different types of mosaicism, including critical review of recent, representative publications for each tumor suppressor gene syndrome • Established criteria for clinical diagnosis of inherited versus mosaic disease, molecular diagnosis, and current methods of genetic analysis Then more extensively, this thesis discusses the most informative, representative original studies for each TSG and provides a summary which covers: • The number of mosaic patients analyzed and the spectrum of clinical features of the cohort they were sampled from • The spectrum of variant allele frequency (VAF), tissue types analyzed, and different analysis methods performed • Whether or not the mosaic patients met clinical criteria for diagnosis of inherited disease • The number of patients who were persistently classified as no mutation identified (NMI) after genetic analysis • Spectrum and type of mosaic mutational event(s) identified • Age of onset and age range of mosaic patients • Patient ascertainment and family history (sporadic or familial cases) and • Type of mosaicism seen Furthermore, it compares and discusses disease severity, possibility of malignancy, and genotype-phenotype correlations for each TSG. Ultimately, by juxtaposing these TSGs, this review aims to centralize existing knowledge about mosaicism and provide insight into how molecular techniques can be broadly applied for better diagnosis of mosaic disease. / 2022-11-10T00:00:00Z

Investigators have discovered thousands of genetic variants associated with various traits using genome-wide association studies (GWAS). These discoveries have substantially improved our understanding of the genetic architecture of many complex traits. Despite the striking success, these trait-associated loci collectively explain relatively little of disease risk. Many reasons for this unexplained heritability have been suggested and two understudied components are hypothesized to have an impact in complex disease etiology: rare variants and gene-environment (GE) interactions. Advances in next generation sequencing have offered the opportunity to comprehensively investigate the genetic contribution of rare variants on complex traits. Such diseases are multifactorial, suggesting an interplay of both genetics and environmental factors, but most GWAS have focused on the main effects of genetic variants and disregarded GE interactions. In this dissertation, we develop statistical methods to detect GE interactions for rare variant analysis for various types of outcomes in both independent and related samples. We leverage the joint information across a set of rare variants and implement variance component score tests to reduce the computational burden. First, we develop a GE interaction test for rare variants for binary and continuous traits in related individuals, which avoids having to restrict to unrelated individuals and thereby retaining more samples. Next, we propose a method to test GE interactions in rare variants for time-to-event outcomes. Rare variant tests for survival outcomes have been underdeveloped, despite their importance in medical studies. We use a shrinkage method to impose a ridge penalty on the genetic main effects to deal with potential multicollinearity. Finally, we compare different types of penalties, such as least absolute shrinkage selection operator and elastic net regularization, to examine the performance of our second method under various simulation scenarios. We illustrate applications of the proposed methods to detect gene x smoking interaction influencing body mass index and time-to-fracture in the Framingham Heart Study. Our proposed methods can be readily applied to a wide range of phenotypes and various genetic epidemiologic studies, thereby providing insight into biological mechanisms of complex diseases, identifying high-penetrance subgroups, and eventually leading to the development of better diagnostics and therapeutic interventions.

No description available.

The demands of multimedia services from mobile user equipment (UE) for achieving high data rate, high capacity and reliable communication in modern mobile wireless systems are continually ever-growing. As a consequence, several technologies, such as the Universal Mobile Telecommunications System (UMTS) and the 3rd Generation Partnership Project (3GPP), have been used to meet these challenges. However, due to the channel fading and the Doppler shifts caused by user mobility, a common problem in wireless systems, additional technologies are needed to combat multipath propagation fading and Doppler shifts. Time-variant channel estimation is one such crucial technique used to improve the performance of the modern wireless systems with Doppler spread and multipath spread. One of vital parts of the mobile wireless channel is channel estimation, which is a method used to significantly improve the performance of the system, especially for 4G and Long Term Evolution (LTE) systems. Channel estimation is done by estimating the time-varying channel frequency response for the OFDM symbols. Time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) technique is a useful channel estimation technique in mobile wireless communication for accurately estimating transmitted information. The main advantage of DPSS or Slepian basis expansion is allowing more accurate representation of high mobility mobile wireless channels with low complexity. Systems such as the fourth generation cellular wireless standards (4G), which was recently introduced in Sweden and other countries together with the Long Term Evolution, can use channel estimation techniques for providing the high data rate in modern mobile wireless communication systems. The main goal of this thesis is to test the recently proposed method, time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) to model the WINNER phase II channel model. The time-variant sub-carrier coefficients are expanded in terms of orthogonal DPS sequences, referred to as Slepian basis expansions. Both Slepian basis expansions and DPS sequences span the low-dimensional subspace of time-limited and band-limited sequences as Slepian showed. Testing is done by using just two system parameters, the maximum Doppler frequency Dmax v and K, the number of basis functions of length N = 256. The main focus of this thesis is to investigate the Power spectrum and channel gain caused by Doppler spread of the WINNER II channel model together with linear fitting of curves for both the Slepian and Fourier basis expansion models. In addition, it investigates the Mean Square Error (MSE) using the Least Squares (LS) method. The investigation was carried out by simulation in Matlab, which shows that the spectrum of the maximum velocity of the user in mobile wireless channel is upper bounded by the maximum normalized one-sided Doppler frequency. Matlab simulations support the values of the results. The value of maximum Doppler bandwidth vDmax  of the WINNER model is exactly the same value as DPS sequences. In addition to the Power spectrum of the WINNER model, the fitting of Slepian basis expansion performs better in the WINNER model than that of the Fourier basis expansion.

Genome-wide Association Studies (GWAS) is the study used to associate common variants and phenotypes and has uncovered thousands of disease-associated variants. However, there is limited research on the contribution of a rare variant. The UK Biobank (UKB) contains detailed medical records and genetic information for nearly 500,000 individuals and offers a great opportunity for genetic association studies on rare variants. Here we focused on the role of rare protein-coding variants on UKB phenotypes. We selected three diseases for analysis: breast cancer, hypothyroidism and type II diabetes. We defined criteria for qualifying variants and pruned the control group to reduce interference signals from similar phenotypes. We identified the most known biomarkers for those diseases, such as BRCA1 and BRCA2 gene for breast cancer, TG and TSHR gene for hypothyroidism and GCK for type II diabetes. This result supports the model validity and clarifies the contribution of rare variants to diseases. Moreover, we also tried the geneset based collapsing method to aggregate information across genes to strengthen the signal from rare variants and build a diagnosis model that only relies on the genetic information. Our model could achieve great performance with an AUC of more than 20% improvement for type II diabetes and breast cancer and more than 90% accuracy for hypothyroidism.

OBJECTIVES: We have previously reported a top-ranked risk gene [i.e., serine incorporator 2 gene (SERINC2)] for alcohol dependence in individuals of European descent by analyzing the common variants in a genome-wide association study. In the present study, we comprehensively examined the rare variants [minor allele frequency (MAF)<0.05] in the NKAIN1-SERINC2 region to confirm our previous finding. MATERIALS AND METHODS: A discovery sample (1409 European-American patients with alcohol dependence and 1518 European-American controls) and a replication sample (6438 European-Australian family participants with 1645 alcohol-dependent probands) were subjected to an association analysis. A total of 39 903 individuals from 19 other cohorts with 11 different neuropsychiatric and neurological disorders served as contrast groups. The entire NKAIN1-SERINC2 region was imputed in all cohorts using the same reference panels of genotypes that included rare variants from the whole-genome sequencing data. We stringently cleaned the phenotype and genotype data, and obtained a total of about 220 single-nucleotide polymorphisms in individuals of European descent and about 450 single-nucleotide polymorphisms in the individuals of African descent with 0

OBJECTIVES: We have previously reported a top-ranked risk gene [i.e., serine incorporator 2 gene (SERINC2)] for alcohol dependence in individuals of European descent by analyzing the common variants in a genome-wide association study. In the present study, we comprehensively examined the rare variants [minor allele frequency (MAF)<0.05] in the NKAIN1-SERINC2 region to confirm our previous finding. MATERIALS AND METHODS: A discovery sample (1409 European-American patients with alcohol dependence and 1518 European-American controls) and a replication sample (6438 European-Australian family participants with 1645 alcohol-dependent probands) were subjected to an association analysis. A total of 39 903 individuals from 19 other cohorts with 11 different neuropsychiatric and neurological disorders served as contrast groups. The entire NKAIN1-SERINC2 region was imputed in all cohorts using the same reference panels of genotypes that included rare variants from the whole-genome sequencing data. We stringently cleaned the phenotype and genotype data, and obtained a total of about 220 single-nucleotide polymorphisms in individuals of European descent and about 450 single-nucleotide polymorphisms in the individuals of African descent with 0